• Journal of Biosystems Engineering
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• v.32 no.1 s.120
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• pp.1-5
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• 2007

This study was conducted to find out effects of abnormal kernels of 0 to 30% in brown rice on quality characteristics during milling using friction type test mill. The average hardness values of abnormal and normal brown rice kernels were 6.52 kg$_f$, 8.48 kg$_f$, respectively. According to the increase of abnormal kernels in brown rice, grain temperature, required electrical energy, the broken kernels ratio, and the weight of solid matter on the surface of milled rice were increased due to crush of the abnormal kernels during milling, which proves that abnormal kernels in brown rice should be removed before milling to improve milling characteristics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.37-43
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• 2020

Recently, many researches have been actively to diagnose symptoms of heart disease using ECG signal, which is an electrical signal measuring heart status. In particular, the electrocardiogram signal can be used to monitor and diagnose arrhythmias that indicates an abnormal heart status. In this paper, we proposed 1-D convolutional neural network for arrhythmias classification systems. The proposed model consists of deep 11 layers which can learn to extract features and classify 5 types of arrhythmias. The simulation results over MIT-BIH arrhythmia database show that the learned neural network has more than 99% classification accuracy. It is analyzed that the more the number of convolutional kernels the network has, the more detailed characteristics of ECG signal resulted in better performance. Moreover, we implemented a practical application based on the proposed one to classify arrythmias in real-time.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.4
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• pp.637-645
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• 2022

Cloud computing has been gaining popularity over decades, and container, a technology that is primarily used in cloud native applications, is also drawing attention. Although container technologies are lighter and more capable than conventional VMs, there are several security threats, such as sharing kernels with host systems or uploading/downloading images from the image registry. one of which can refer to the integrity of container images. In addition, runtime security while the container application is running is very important, and monitoring the behavior of the container application at runtime can help detect abnormal behavior occurring in the container. Therefore, in this paper, first, we implement a signing checker that automatically checks the signature of an image based on the existing Docker Content Trust (DCT) technology to ensure the integrity of the container image. Next, based on falco, an open source project of Cloud Native Computing Foundation(CNCF), we introduce newly created image for the convenience of existing falco image, and propose implementation of docker-compose and package configuration that easily builds a monitoring system.

• Research in Plant Disease
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• v.17 no.1
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• pp.19-24
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• 2011

It was identified as a sharp eyespot (Rhizoctonia cerealis) that the isolates from abnormal symptoms in wheat that showed yellowing leaves, necrotic spot on stem base and dead tillers. These isolates have slower growth property and fewer mycelia than Rhizoctonia solani AG-1(1A) (KACC 40106). They showed binuclear cell, same media cultural and DNA characteristics to R. cerealis. They caused same symptoms on leaves and stem base appeared in artificial inoculation test, comparing to diseased wheat fields and also affect to maturing of kernels. They have optimal growth temperature and acidity on the artificial media as $20{\sim}25^{\circ}C$ and pH 5~7, respectively. In the investigation of varietal resistance of Korean winter cereal crops to sharp eyespot, there was no resistant in wheat cultivars that all materials infected over 20% diseased ratio. 12 cultivars including 'Anbaekmil', however, considered to moderate resistance with 20 to 30% infection ratio. The others crops using in feeding, whole crop barley, oat, rye and triticale were resistant below 15% diseased degree except the rye that showed over 50% infection rate. It was the first evaluation to sharp eyespot resistance for the Korean feeding crop cultivars. Most tested Korean barley cultivars for malting and food were moderate and susceptible to the sharp eyespot. Only 3 hulled barley, 'Tapgolbori', 'Albori' and 'Seodunchalbori', showed resistance with less than 10% diseased ratio. All tested naked barley cultivars showed susceptible response to the disease.